Renewable Energy Production Research Articles

Green hydrogen in Africa: opportunities and limitations

Green hydrogen is globally seen as a universal fuel, feedstock or energy carrier and storage. The study aims to examine the role of the emerging green hydrogen market in developing countries in Africa. The goal is to indentify key factors that may either positively or negatively affect the development of green hydrogen energy in Africa. Several developing countries have been identified as potential key players in green hydrogen production: South Africa, Egypt, Morocco, and Namibia. These countries are expected to play a vital part in the development of hydrogen technologies due to favourable climatic conditions for the production of low-cost renewable energy, the possibility of exporting hydrogen to EU countries, and the presence of various national policy initiatives (national hydrogen strategies) and international partnerships (the Africa Green Hydrogen Alliance). The results showed that green hydrogen will boost economic development in African countries, stimulate investment and create new jobs. The study also identifies several barriers that could affect the development of green hydrogen in Africa: high investment costs for hydrogen infrastructure, financing, weak institutions, water scarcity and the imbalance between hydrogen for local use and for export.

Biomass-Solar Energy: A Comprehensive Review of Sustainable Energy Generation

India is the world's most populous country and plays a crucial role in achieving the United Nations' Sustainable Development Goals by 2030. SDG No. 7 (affordable and clean energy) and climate change reduction goals are essential for sustainable development. This review discusses clean energy potential, obstacles and stimulants, and renewable energy policies in India, focusing on solar and biomass resources. With biomass resources, the nation can generate 130 million tonnes of oil equivalent annually, and it can generate 5,000 trillion kWh of solar energy annually. For the production of renewable energy, biomass resources such as Jatropha, sweet sorghum, cassava, rice, coconut, and agricultural leftovers can be employed. The purpose of this review is to highlight the benefits of using bioenergy to achieve a sustainable energy future through financial incentives, enhanced research, public awareness, social amenities, strategic replenishment, and productive intergovernmental collaborations. Solar thermal and photovoltaic systems offer great possibilities for grid-connected, off-grid, and hybrid installations. Site-specific considerations such as incentives, financing, research, public awareness, government regulations, and private investments influence the techno-economic viability and environmental relevance of solar power and bioenergy for India's sustainable development.

Optimal scheduling of a RES – Electrolyzer aggregator in electricity, hydrogen and green certificates markets

The emerging threat of climate change underscores the necessity for increased investments in renewable energy sources and hydrogen energy to enhance the transition towards a more sustainable and resilient future. This work presents a simple Linear Programming (LP) mathematical framework to ensure the optimal portfolio management and participation of an aggregator owning a Polymer Electrolyte Membrane (PEM) electrolyzer and renewable energy assets in the electricity, hydrogen and green certificates markets. The objective aims to maximize the aggregator's overall profits by optimally managing green certificates issuance and diminishing the curtailment of the renewable energy production. The proposed approach is applied to an illustrative case study, while additionally a number of scenarios are considered to account for fluctuations in electricity price and wind power production. Furthermore, the impact of expanding electrolyzer's power capacity from the aggregator's side is also investigated. The results obtained illustrate the impact of the above-mentioned scenarios on the optimal operation and profitability of the aggregator.

Predictive analysis of methane-enhanced conversion of organic waste into sustainable fuel: A machine learning approach

Currently, methane-assisted biomass-to-fuel (M-BtF) processes are being introduced, which are of considerable importance due to the production of an environmentally friendly fuel. Due to the lower price, natural gas can address a stronger potential compared to hydrogen and nitrogen under pyrolysis and bio-oil upgrading processes. Based on this, it seems vital to evaluate such a clean fuel production process from the standpoints of the life cycle analysis (LCA) and techno-economic assessment to exhibit the economic feasibility and environmental superiority. This article aims to utilize machine learning (ML) to predict the yield of organic solid waste, evaluate its economic feasibility, and investigate the environmental sustainability of the valorization of a methane-assisted organic solid waste process. The study employs an artificial neural network (ANN) model with a semi-automatic tuning procedure to forecast the yield of bio-oil, based on biomass characterization. This approach eliminates the need for pilot plant trials for new types of biomass to determine process yields before industrial scale-up. The ANN model demonstrated a high prediction accuracy, achieving an R2 (coefficient of determination) value higher than 0.82. The simulation results, derived from the ML predictions, were then employed in the techno-economic analysis and LCA, where they were compared with other commercial processes for economic viability and environmental impact assessments. The minimum selling price for the renewable diesel was calculated as 3.45 US$/gallon, which is notably competitive, being around 26 % lower than the average minimum selling price observed in relevant publications. Based on Monte Carlo simulation, the plant's internal rate of return (IRR) remained above 50 % across various discount rates, suggesting a highly profitable investment. From LCA results, the proposed method was found to emit ∼ 67 % less greenhouse gases (GHG) compared to standard commercial processes. Overall, the study showcases how the integration of machine learning into process simulation can lead to both economically and environmentally beneficial outcomes, particularly in the context of renewable energy production.

The impact of taxation, technological innovation and trade openness on renewable energy investment: Evidence from the top renewable energy producing countries

In the context of contemporary global warming, transitioning from traditional fossil energy to renewable energy sources emerges as a crucial strategy to reduce carbon emissions and achieve the 7th sustainable development goal (SDG). Tax policy significantly shapes the investment landscape, influencing all factors concerning the transition to renewable energy, such as technological innovation and trade openness. However, no empirical studies have examined the direct and moderating role of taxation on renewable energy investment, mainly due to the scarcity of tax data. Therefore, this paper utilizes the recently released Government Revenue Dataset (2023) to explore the complex link between taxation, technological innovation, trade openness, and renewable energy investment for a sample of the top 37 renewable energy-producing countries during the period (1996–2021). The results of the cross-section ARDL (CS-ARDL) and the pooled mean group ARDL (PMG-ARDL) models indicate that taxation has a negative and significant influence on renewable energy investment across all model specifications, both in the short and long run. Conversely, innovation and trade openness exhibit a positive and significant influence on clean energy investment. Regarding the moderating influence of taxation, the results revealed that tax revenues depress the positive impact exerted by technological innovation and international trade. Furthermore, the fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models affirm the robustness of the long-run results obtained from CS-ARDL and PMG-ARDL models. The study's findings offer significant insights into how countries engaged in renewable energy production can enhance their taxation framework to leverage trade and innovation to promote renewable energy investment.

Contextualizing Polarimetric Retrievals of Boundary Layer Height Using State-of-the-Art Boundary Layer Profiling

Abstract Knowledge about the depth of the planetary boundary layer (PBL) is crucial for a variety of applications, but direct observations of PBL depth are spatiotemporally sparse. Recent studies have proposed using operational dual-polarization weather radars to observe the evolution of PBL depth by capitalizing on unique differential reflectivity (ZDR) signatures of Bragg scatter at the top of the PBL. While this approach appears promising and cost-effective, uncertainties remain about the representativeness of these estimates and how its efficacy may vary by geography and climatology. To address these outstanding uncertainties, this study compares collocated observations collected from two WSR-88D radars and two state-of-the-art mobile boundary layer profiling systems and evaluates the proposed methodology over the full diurnal cycle. Results indicate good overall correspondence between the profiling- and radar-based PBL depth estimates, with an abrupt divergence during the early evening transition and large discrepancies overnight. Relatively large root-mean-square-deviations (RMSDs) coupled with small biases match expectations when comparing spatially averaged data with point observations during PBL growth, which capture frequent fluctuations. A qualitative examination of the radar data reveals signatures of elevated residual layers, clouds, and ground clutter, all of which can obfuscate the desired surface-based PBL signal but which may have their own utility. The prominence of the Bragg scatter signal is found to be correlated with the observed moisture gradient at the top of the PBL, reflecting climatological variability that should be considered. These findings motivate further work to improve the automated detection of Bragg scatter layers from polarimetric radar data. Significance Statement Knowledge of the height of the planetary boundary layer matters for weather forecasting, air quality, and renewable energy production. Currently, boundary layer height measurements are taken at select locations twice a day. However, a method to use the existing national network of polarimetric weather radars for this purpose has been proposed. This work evaluates this method against specialized boundary layer measurements. The results show that the method is generally reliable during the daytime and could be used for a variety of applications including climatologies and model evaluation. There remain a number of situational caveats, including residual turbulence, clouds/precipitation, ground clutter, and certain meteorological environments, that may require modification of the approach and need to be considered in future work.

CeO2-CuO composites prepared via supercritical antisolvent precipitation for photocatalytic hydrogen production from lactic acid aqueous solution

The global increase in energy demand requires a continuous search for renewable and clean alternative resources to fossil fuels. Hydrogen is emerging as a promising energy carrier for the future; its production via photocatalysis, driven by sunlight, can directly convert solar energy into a usable or storable energy resource. However, water splitting requires sacrificial agents or electron donors/hole scavengers, such as short-chain organic acids. This research explores the use of lactic acid as a source for photocatalytic hydrogen production, offering valuable alternatives for wastewater management and renewable energy production. This study employed the innovative supercritical antisolvent (SAS) technique to micronize the precursors of both the active phase (CeO2) and co-catalyst (CuO), ensuring rapid and complete solvent removal and size reduction of photocatalyst precursors. The prepared samples were characterized by field emission scanning electron microscopy (FESEM), Fourier transform infrared (FT-IR) spectroscopy, dynamic light scattering (DLS) analysis, Brunauer-Emmett-Teller (BET) analysis and thermogravimetric analysis (TGA). This study has shown that the micronization process resulted in a notable improvement in CeO2 photocatalytic activity, attributed to the reduction of the dimensions of the powders. Hydrogen production was equal to 3989 μmol L−1 for the SAS-produced photocatalyst while using a commercial CeO2 sample resulted in H2 production of 2519 μmol L−1. The enhanced photoactivity of CeO2-CuO composites was found to be related to the presence of CuO. The optimal CuO amount was equal to 0.5 wt%, determining a hydrogen production of 9313 μmol L−1 after 4 h of UV irradiation time. A photocatalytic test carried out with deuterated water (D2O) instead of distilled H2O demonstrated that hydrogen was preferentially produced from water splitting reaction, whereas lactic acid acted as a sacrificial agent being oxidized from positive holes photogenerated in the valence band of CuO.

Capacity Degradation Assessment of Lithium-Ion Battery Considering Coupling Effects of Calendar and Cycling Aging

Capacity degradation of lithium-ion batteries largely determines the cost, performance and environmental impact of various products such as renewable energy production systems, portable electronics, and electric vehicles. Degradation assessment is thus of great importance for prognostic and health management of batteries, which ensures a stable production and operation. There are typically two leading sources contributing to the degradation of a lithium-ion battery, namely, cycling aging during charge/discharge cycles and calendar aging during idle states. However, most existing studies on degradation assessment either only consider a single source or ignore the coupling of these two sources, which makes the evaluation inefficient. A common observation in practice is that a battery tends to degrade faster when it experiences charge/discharge cycles continuously for a longer time. To capture this feature, this paper introduces the concept of the cumulative uninterrupted cycling duration (CUCD), which is defined as the consecutive operation duration since a battery ends the idle state. The CUCD can also help to model the coupling between the calendar and cycling aging. This paper then proposes to model the drift rate of cycling aging as a function of the CUCD and the functional form is determined with the monotonic spline. We estimate the model parameters by maximizing the likelihood function. Hypothesis testings toward the significance of the coupling between two aging sources and the monotonicity of the drift rate function under cycling aging are also provided. The effectiveness and the superiority of the model are validated using numerical and real case studies. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This study aims to characterize the degradation of lithium-ion battery simultaneously considering calendar and cycling agings and the coupling effect. Unlike previous research that only supplied experimental results to qualitatively illustrate the existence of the coupling effect between these two aging sources, this study provides procedures to quantitatively test the significance of such an effect. In addition, previous research ignored the coupling effect in the degradation modeling as it is difficult to capture, this study propose the concept of CUCD to characterize it. The CUCD is also introduced as a stress factor for cycling aging, which is based on the fact that a battery will degrade faster when it experiences charge/discharge cycle continuously for a longer time. Hypothesis testing is also provided to illustrate this monotonicity. To deal with another challenge that the expert knowledge of the functional form between cycling aging and CUCD is unavailable except for the monotonicity, a nonparametric method with the shape-restricted spline is adapted. The estimation procedures for the model parameters are also presented.

The Impact of Economic Growth on the Ecological Environment and Renewable Energy Production: Evidence from Azerbaijan and Hungary

This article reflects on the necessity of employing renewable energy sources in the modern era to mitigate the negative environmental impact caused by traditional energy sources and address environmental pollution. Through research conducted in Azerbaijan and Hungary, it analyses the influence of economic growth on the ecological environment and renewable energy production. Due to limitations in the general dataset, the study considers the period of 1997–2022 for CO2 emissions causing environmental pollution, 2007–2022 for renewable energy production in Azerbaijan, and 2000–2021 for the same in Hungary. Information regarding wind and solar energy in Azerbaijan has been available since 2013. Temporal sequences have been utilised in the research, employing Augmented Dickey–Fuller and Phillips–Perron (PP) unit root tests to examine the stationarity of the time series. An Autoregressive Distributed Lag (ARDL) model has been constructed, and the credibility of the model has been verified using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) models. The findings reveal that in Azerbaijan, the long-term impact of economic growth on hydro-energy has been negative, while dependence on biomass and waste has been insignificant but positive. The influence on wind and solar energy production has also been negative and insignificant, akin to hydro-energy production. However, energy supply from renewable sources has been positively affected by the aggregate indicator of economic growth, albeit insignificantly. The impact of economic growth on carbon dioxide has been significant in two magnitudes, whereas in other cases, it has been insignificant but positive. In Hungary, economic growth has positively affected renewable energy production. However, the impact on carbon dioxide has been negative, meaning that this indicator has decreased as economic growth has increased. The study concludes that the impact of economic growth on indicators of both countries has been more effective in Hungary, which can be attributed to economic development.

Analysis of Morocco's renewable energy production and transmission potential

Analysis of Morocco's renewable energy production and transmission potential

PRODUCTION OF VALUE-ADDED BIOCHAR AND BIO-OIL FROM MICROWAVE CO2 PYROLYSIS OF MEDIUM-DENSITY FIBERBOARD WASTE

This study investigates the feasibility of using microwave CO2 pyrolysis to dispose of medium-density fibreboard (MDF) waste, a significant by-product of the furniture manufacturing industry. The primary goal is to transform MDF waste into valueadded biochar and bio-oil, exploring an alternative to conventional pyrolysis methods that typically use nitrogen (N2) as a purge gas. The research emphasises the potential benefits of CO2 utilisation in pyrolysis, both to enhance the quality of biochar and bio-oil and as a strategy for greenhouse gas (GHG) mitigation. This research reveals that conducting microwave pyrolysis in a CO2 atmosphere increases biochar (up to 44.8%) and bio-oil (up to 21.2%) yields over N2 pyrolysis. CO2 hinders volatile thermal cracking and aids in gas defragmentation and repolymerisation, with biochar yield rising with time and biooil peaking at an optimal duration. This study underscores microwave CO2 pyrolysis as a promising alternative for converting biomass waste into valuable products, potentially contributing to fuel utilisation. It also highlights the environmental benefits of this method, particularly in terms of CO2 utilisation, aligning with the broader objectives of sustainable waste management and renewable energy production. The findings provide a basis for future research in this area, focusing on optimising process parameters, exploring potential applications of bio-products, and assessing the economic and environmental viability of this innovative approach.

Generation of Biogas Using Cow Dung With Organic Waste in the Presence of Iron Filings

In recent years, major issues such as demographic growth, food security, and exploitation of natural resources have raised worries worldwide. To handle these issues and the environment in an eco-friendly manner, a shift has been made from the mere exploitation of natural resources to their recovery and reuse. The production of organic waste is increasing dramatically. Anaerobic digestion (AD) with related biogas production is regarded as a substitute for waste management strategies such as landfilling and incineration of municipal solid waste (MSW). Biogas systems protect air, water, and soil by recycling organic waste into renewable energy and soil products while reducing greenhouse gas emissions. The present study aimed to establish a biogas system that involves co-digestion and iron filings. Specifically, it investigated the AD of vegetable waste combined with cow dung and Jatropha seed cake with iron filings. The experiment was conducted over 60 days by four digesters (S1, S2, S3, and S4) containing mixtures of cow dung and vegetable waste (S1), cow dung and Jatropha seed cake (S2), cow dung and vegetable waste with 10 g of iron filings (S3), and cow dung and Jatropha seed cake with 10 g of iron filings (S4). After 60 days, the amount of biogas collected from the digesters S1, S2, S3, and S4 was 172.9 mL/gVS, 205.64 mL/gVS, 186.086 mL/gVS, and 231.25 mL/gVS, respectively. The sample mixture of digester S4, which contained cow dung and Jatropha seed cake with iron filings, resulted in the maximum yield of biogas production due to the iron additive potential for accepting and donating electrons.

Multi-actor approach to manage the water-energy-food nexus at territory scale

This study presents an innovative water-energy-food nexus (WEFN) generic multi-actor multi-level framework that simulates dynamic nexus systems and generates optimal resource management schemes and land-use allocation scenarios. The framework combines operational integrated multi-agent based simulations, dynamic agro-hydrological and renewable energy generation units (solar and wind) models and multi-criteria decision-making methods. It has been applied to a case study area of 800 km2 located downstream the Aveyron watershed, in Southwestern France. Local and regional strategic multi-criteria decision-making settings are compared. Under the local decision-making setting land-use allocation decisions are taken at agricultural parcel level whereas under the regional decision-making settings a single land allocation decision is taken for the whole territory. Possible land allocations are either crop rotations allocations, renewable energy generation units allocations or a mix of both. The framework is useful to generate scenarios of spatial allocations of renewable energy production units in an agricultural watershed facing water scarcity.

An Effective Strategy for Achieving Economic Reliability by Optimal Coordination of Hybrid Thermal–Wind–EV System in a Deregulated System

This paper describes an effective operating strategy for electric vehicles (EVs) in a hybrid facility that leverages renewable energy sources. The method is to enhance the profit of the wind–thermal–EV hybrid plant while maintaining the grid frequency (fPG) and energy level of the EV battery storage system. In a renewable-associated power network, renewable energy producers must submit power supply proposals to the system operator at least one day before operations begin. The market managers then combine the power plans for the next several days based on bids from both power providers and distributors. However, due to the unpredictable nature of renewable resources, the electrical system cannot exactly adhere to the predefined power supply criteria. When true and estimated renewable power generation diverges, the electrical system may experience an excess or shortage of electricity. If there is a disparity between true and estimated wind power (TWP, EWP), the EV plant operates to minimize this variation. This lowers the costs associated with the discrepancy between actual and projected wind speeds (TWS, EWS). The proposed method effectively reduces the uncertainty associated with wind generation while being economically feasible, which is especially important in a deregulated power market. This study proposes four separate energy levels for an EV battery storage system (EEV,max, EEV,opt, EEV,low, and EEV,min) to increase system profit and revenue, which is unique to this work. The optimum operating of these EV battery energy levels is determined by the present electric grid frequency and the condition of TWP and EWP. The proposed approach is tested on a modified IEEE 30 bus system and compared to an existing strategy to demonstrate its effectiveness and superiority. The entire work was completed using the optimization technique called sequential quadratic programming (SQP).

A second life for mining waste as an amendment for soil remediation

Mining is a cornerstone of the productive system, particularly in sectors, such as renewable energy and electronic equipment production, where its significance is anticipated to grow in the coming years. Aligned with the principles of Nature-Based Solutions and Zero Waste policies, recycling mining waste as soil amendments could concurrently restore degraded areas and reduce the disposal of mining waste. In this context, we aimed to remediate a post-mining soil primarily impacted by heavy metal pollution using an alkaline waste generated in dunite exploitation, either in combination with compost or independently in field conditions. The objectives were to minimize heavy metal(loid)s mobility (As, Cu, Cd, Ni, Pb, and Se), to improve soil health, and stimulate plant growth (phytoremediation, Lolium perenne L. was used). Results revealed that the combination of dunite and compost successfully reduced the concentrations of available Cu and Ni in the soil by more than four times, significantly enhanced soil properties, and promoted the harvest of a greater biomass. Additionally, Lolium perenne L. demonstrated phytostabilizing capacity for Cu and Ni in the soil treated with the amendments. In conclusion, the utilization of combined dunite-based and organic amendments proves to be a favorable strategy for restoring polluted post-mining soils.

Design of an Electric Vehicle Charging System Consisting of PV and Fuel Cell for Historical and Tourist Regions

One of the most important problems in the widespread use of electric vehicles is the lack of charging infrastructure. Especially in tourist areas where historical buildings are located, the installation of a power grid for the installation of electric vehicle charging stations or generating electrical energy by installing renewable energy production systems such as large-sized PV (photovoltaic) and wind turbines poses a problem because it causes the deterioration of the historical texture. Considering the need for renewable energy sources in the transportation sector, our aim in this study is to model an electric vehicle charging station using PVPS (photovoltaic power system) and FC (fuel cell) power systems by using irradiation and temperature data from historical regions. This designed charging station model performs electric vehicle charging, meeting the energy demand of a house and hydrogen production by feeding the electrolyzer with the surplus energy from producing electrical energy with the PVPS during the daytime. At night, when there is no solar radiation, electric vehicle charging and residential energy demand are met with an FC power system. One of the most important advantages of this system is the use of hydrogen storage instead of a battery system for energy storage and the conversion of hydrogen into electrical energy with an FC. Unlike other studies, in our study, fossil energy sources such as diesel generators are not included for the stable operation of the system. The system in this study may need hydrogen refueling in unfavorable climatic conditions and the energy storage capacity is limited by the hydrogen fuel tank capacity.

Optimization scheduling for low-carbon operation of building integrated energy systems considering source-load uncertainty and user comfort

Hydrogen, being a clean energy source, presents novel possibilities for the efficient exploitation of building energy. Nevertheless, the unpredictability in the production of renewable energy, the fluctuating demand from users, and the varying comfort needs within buildings provide substantial obstacles to the functioning of building energy systems. This work suggests an optimal technique for managing a comprehensive energy system based on hydrogen. The strategy takes into account the variability in energy sources and the need for user satisfaction. Firstly, a model of building integrated energy system (BIES) is created, which includes devices for utilizing hydrogen due to its adaptable qualities. Afterwards, the adaptable attributes of electrical, cooling, and heating loads within the building are carefully examined, resulting in the creation of a integrated demand response (IDR) model and a user-integrated comfort rating model. Moreover, a ladder-type carbon tax framework is implemented, employing robust optimization methods to tackle uncertainty in the production of renewable energy and demand. Finally, a model for optimizing the scheduling of energy system operation is formulated. A case analysis is performed utilizing a spacious office building located in the northern region as an instructive example. The findings indicate that the suggested approaches successfully control user involvement in demand response, decrease carbon emissions in the system, improve user energy comfort, and accomplish the economic, low-carbon, and comfortable functioning of BIES.

From Nature to Technology: Exploring the Potential of Plant-Based Materials and Modified Plants in Biomimetics, Bionics, and Green Innovations.

This review explores the extensive applications of plants in areas of biomimetics and bioinspiration, highlighting their role in developing sustainable solutions across various fields such as medicine, materials science, and environmental technology. Plants not only serve essential ecological functions but also provide a rich source of inspiration for innovations in green nanotechnology, biomedicine, and architecture. In the past decade, the focus has shifted towards utilizing plant-based and vegetal waste materials in creating eco-friendly and cost-effective materials with remarkable properties. These materials are employed in making advancements in drug delivery, environmental remediation, and the production of renewable energy. Specifically, the review discusses the use of (nano)bionic plants capable of detecting explosives and environmental contaminants, underscoring their potential in improving quality of life and even in lifesaving applications. The work also refers to the architectural inspirations drawn from the plant world to develop novel design concepts that are both functional and aesthetic. It elaborates on how engineered plants and vegetal waste have been transformed into value-added materials through innovative applications, especially highlighting their roles in wastewater treatment and as electronic components. Moreover, the integration of plants in the synthesis of biocompatible materials for medical applications such as tissue engineering scaffolds and artificial muscles demonstrates their versatility and capacity to replace more traditional synthetic materials, aligning with global sustainability goals. This paper provides a comprehensive overview of the current and potential uses of living plants in technological advancements, advocating for a deeper exploration of vegetal materials to address pressing environmental and technological challenges.

Pengaruh Penerapan Ekonomi Hijau Terhadap Peningkatan Pendapatan Pada PT. Pertamina Geothermal Energy Tbk.

This study explores the impact of green economy implementation on revenue generation in the renewable energy sector in Indonesia, with a focus on PT Pertamina Geothernal Energy Tbk. Regression analysis shows that total electricity equivalent production has a significant effect on increasing the company's net profit, while government investment does not show a significant effect. These results suggest that increasing renewable energy production is one of the key factors in increasing revenue in this sector. The study also identified strategies to maximize the economic and environmental benefits of the transition to clean energy. These strategies include regulatory and policy reforms, effective management of public investment, and development of people- and environment-oriented policies. Implementing a green economy in Indonesia's renewable energy sector has the potential to increase revenues, promote sustainable economic growth, and preserve the environment.

DIGITAL FOUNDATIONS FOR BUSINESS DEVELOPMENT IN THE FIELD OF RENEWABLE ENERGY

The article focuses on specifying the digital foundations for the development of entrepreneurship in the field of alternative energy. It's proven that these technologies are a catalyst for innovation, process optimization, and the creation of new business models that contribute to the industry's sustainable development. The components that guide the digitalization of processes related to the production, distribution, storage, and sale of electricity have been identified in the following areas: intelligent energy systems, Internet of Things networks and Big data systems, digital platforms, and marketplaces. The components that adjust the digital development of each individual or company engaged in business related to the production, distribution, storage, or sale of renewable energy have been identified in the following areas: 3D printing, robotics, and blockchain technology. It has been established that the digital foundations for thе entrepreneurship development in the field of alternative energy are directed towards process optimization, increased efficiency, cost reduction, and the creation of new business models.